AI News, When Thinking About Artificial Intelligence, Don't Forget the People

When Thinking About Artificial Intelligence, Don't Forget the People

Businesses that adopt artificial intelligence technology to help with jobs like automating call center activity must also consider giving employees education and training so that those who are displaced by innovation can still work.

Companies like Amazon (amzn) and Google (goog) are using AI to improve their digital assistants, those voice operated helpers on smartphones and home automation hubs, said Accenture chief technology officer Paul Daugherty during a Wednesday media event.

Additionally, business leaders must be more involved with public education to ensure that it is properly training the next generation to become “life-long” learners who are willing to adapt as technology continuously advances.

Companies looking to invest in AI should be aware that the hype behind it has led vendors to claim they have the latest answer to every business problem, said Jerry Kaplan, a computer scientist and entrepreneur who spoke at the event.

AI’s PR Problem

HBO’s Westworld features a common plot device—synthetic hosts rising up against their callous human creators.

While it’s true that today’s machines can credibly perform many tasks (playing chess, driving cars) that were once reserved for humans, that doesn’t mean that the machines are growing more intelligent and ambitious.

Jacquard looms replaced expert needleworkers in the 19th century, but these remarkable devices—programmed with punch cards for a myriad of fabric patterns—didn’t spell doom for dressmakers and tailors.

Now that comparably capable devices are given away as promotional trinkets at trade shows, the mathematically minded among us can focus on tasks that require broader skills, like statistical analysis.

Soon, your car will be able to drive you to the office upon command, but you don’t have to worry about it signing up with Uber to make a few extra bucks for gas while you’re in a staff meeting (unless you instruct it to).

They power recommendation systems on Amazon and Netflix, hone Google search results, describe videos on YouTube, recognize faces, trade stocks, steer cars, and solve a myriad of other problems where big data can be brought to bear.

I’d suggest that one problem with AI is the name itself—coined more than 50 years ago to describe efforts to program computers to solve problems that required human intelligence or attention.

Perhaps a less provocative description would be something like “anthropic computing.” A broad moniker such as this could encompass efforts to design biologically inspired computer systems, machines that mimic the human form or abilities, and programs that interact with people in natural, familiar ways.

Rather, we should resist our predisposition to attribute human traits to our creations and accept these remarkable inventions for what they really are—potent tools that promise a more prosperous and comfortable future.

‘Artificial Intelligence’ Has Become Meaningless

But even a simple machine-learning system like Netflix’s dynamic optimizer, which attempts to improve the quality of compressed video, takes data gathered initially from human viewers and uses it to train an algorithm to make future choices about video transmission.

As the bot author Allison Parrish puts it, “whenever someone says ‘AI’ what they're really talking about is ‘a computer program someone wrote.’” Writing at the MIT Technology Review, the Stanford computer scientist Jerry Kaplan makes a similar argument: AI is a fable “cobbled together from a grab bag of disparate tools and techniques.” The AI research community seems to agree, calling their discipline “fragmented and largely uncoordinated.” Given the incoherence of AI in practice, Kaplan suggests “anthropic computing” as an alternative—programs meant to behave like or interact with human beings.